End-To-End-Wine-Quality-Machine-Learning-Project

This is End to End machine learning Project i need to use diffrent tech stacks including EC2,ECR,Github actions and S3-bucket , flask m html & css for ui

Tool you have to install:-

1. Anaconda: https://www.anaconda.com/
2. Vs code: https://code.visualstudio.com/download
3. Git: https://git-scm.com/

Data link:

• Kaggle: https://www.kaggle.com/datasets/yasserh/wine-quality-dataset/data

How to run?

git clone https://github.com/IbraahimLab/End-To-End-Wine-Quality-Machine-Learning-Project

conda create -n wine python=3.10 -y

conda activate wine

pip install -r requirements.txt

Create Mongo db ATLAS

here : https://www.mongodb.com/products/platform/atlas-database

1. Login to AWS console.

2. Create IAM user for deployment

#with specific access

1. EC2 access : It is virtual machine

2. ECR: Elastic Container registry to save your docker image in aws

3. S3 Fullacces

Export the environment variable

export MONGODB_URL="Your mongo db url"

export AWS_ACCESS_KEY_ID=<Your AWS_ACCESS_KEY_ID>

export AWS_SECRET_ACCESS_KEY=<Your AWS_SECRET_ACCESS_KEY>

3. Create ECR repo to store/save docker image

- Save the URI: in temporary place you will put on github action 

4. Create EC2 machine (Ubuntu)

5. Open EC2 and Install docker in EC2 Machine:

#optinal

sudo apt-get update -y

sudo apt-get upgrade

#required

curl -fsSL https://get.docker.com -o get-docker.sh

sudo sh get-docker.sh

sudo usermod -aG docker ubuntu

newgrp docker

6. Configure EC2 as self-hosted runner:

setting>actions>runner>new self hosted runner> choose os> then run command one by one

7. Setup github secrets:

• AWS_ACCESS_KEY_ID
• AWS_SECRET_ACCESS_KEY
• AWS_DEFAULT_REGION
• ECR_REPO
• MONGODB_URL